KR101425142B1 - Interference cancelling method for cooperative communication system - Google Patents

Abstract

A method for eliminating inter-relay interference in a cooperative communication system includes the steps of (a) combining two data symbol blocks at a source node, (b) performing inverse Fourier transform (IDFT) on data symbol blocks at a source node, (C) transmitting data symbol blocks in the relay node and performing signal processing operations to the destination nodes by inserting the CPs into the relay node; (d) Removing the cyclic prefix from the data symbol block and performing Fourier transform (DFT) on the data dumbbell convex, and (e) removing interference using either the ZF scheme, the MMSE scheme, or the MLSE scheme at the destination node . Step (e) is a step of determining an optimal interference cancellation scheme by using one of ZF scheme, MMSE scheme, and MLSE scheme based on a reference BER value, reference communication information, and complexity of interference cancellation scheme, and applying a technique determined by an optimal interference cancellation scheme Thereby eliminating interference.

Description

{INTERFERENCE CANCELING METHOD FOR COOPERATIVE COMMUNICATION SYSTEM}

The present invention relates to a method for eliminating inter-relay interference in a cooperative communication system.

A collaborative communication system is a communication system that obtains cooperative diversity gain by cooperatively transmitting signals to a destination node using a plurality of distributed relay nodes (A. Nosratinia, TE Hunter, and A. Hedayat, "Cooperative communication in wireless networks, "IEEE Commun. Mag., Vol. 42, No. 10, pp. 74-80, Oct. 2004).

When several cooperative communication systems exist in a narrow space or share a destination node with multiple antennas, the signals transmitted from each relay node will interfere with each other, thereby causing a bit error rate : BER). Various studies for eliminating interference have been conducted (C. Shen, Y. Zhu, S. Zhou and J. Jiang, "On the performance of V-blast with zero-forcing successive interference cancellation receiver," IEEE Commun. Society, vol. 5, pp. 2818-2822, Dec. 2004.).

The present invention seeks to eliminate interference occurring in a cooperative communication system.

The present invention seeks to eliminate interference by applying techniques used in other fields to cooperative communication systems.

The present invention attempts to eliminate interference using an optimal technique among the ZF technique, the MMSE technique, and the MLSE technique according to the communication environment and conditions.

The solution of the present invention is not limited to those mentioned above, and other solutions not mentioned can be clearly understood by those skilled in the art from the following description.

A method for eliminating inter-relay interference in a cooperative communication system according to the present invention includes: a step of transmitting a signal from a source node to a destination node through a relay node in a cooperative communication system; To remove the interference.

The interference cancellation step may include determining an optimal interference cancellation scheme based on the reference BER value, the base communication information, and the complexity of the interference cancellation scheme, one of ZF scheme, MMSE scheme, or MLSE scheme, To remove the interference. In this case, the reference communication information may include at least one of an SNR estimation value or channel coefficient information for MLSE technique application.

In the step of determining the optimal interference cancellation scheme, the MMSE scheme is excluded from the candidate group when the SNR estimation value is not included in the reference communication information in the candidate group including the ZF scheme, the MMSE scheme, and the MLSE scheme. In the case of two or more interference cancellation schemes remaining in the candidate group, the interference cancellation technique with an error rate higher than the reference BER value according to the transmission power among the interference cancellation techniques remaining in the candidate group is performed in the candidate group And removing only the interference cancellation technique having the lowest complexity among the interference cancellation schemes remaining in the candidate group if there are more than two interference cancellation schemes remaining in the candidate group.

In order to detect the signal transmitted from the target transmitting node, the ZF technique uses a result obtained by multiplying the received symbol at the destination node by the inverse matrix of the channel coefficient matrix. In order to detect a signal transmitted from the target transmitting node, The MLSE technique is a technique of convolutionally coding the symbol node transmitted from the source node and transmitting the symbol node transmitted at the ith transmitted bit sequence estimated after the Alamouti demodulation. The Euclidean distance between the bit streams of the signal having the same symbol bit number as the bit stream is calculated to select the bit stream having the smallest value.

In another aspect of the present invention, a method for eliminating inter-relay interference in a cooperative communication system includes the steps of (a) combining two data symbol blocks at a source node, (b) performing inverse Fourier transform (IDFT) (C) transmitting a data symbol block at a relay node, performing a signal processing operation to the relay node, and transmitting the data symbol block to a destination node; (d) ) Removing the cyclic prefix from the data symbol block received from the destination node and performing a Fourier transform (DFT) on the data dumbbell convex, and (e) using the ZF scheme, MMSE scheme, or MLSE scheme at the destination node And removing the interference.

Step (e) is a step of determining an optimal interference cancellation scheme by using one of ZF scheme, MMSE scheme, and MLSE scheme based on a reference BER value, reference communication information, and complexity of interference cancellation scheme, and applying a technique determined by an optimal interference cancellation scheme Wherein the reference communication information includes at least one of an SNR estimate or channel coefficient information for MLSE technique application.

In the step of determining the optimal interference cancellation scheme, the MMSE scheme is excluded from the candidate group when the SNR estimation value is not included in the reference communication information in the candidate group including the ZF scheme, the MMSE scheme, and the MLSE scheme. In the case of two or more interference cancellation schemes remaining in the candidate group, the interference cancellation technique with an error rate higher than the reference BER value according to the transmission power among the interference cancellation techniques remaining in the candidate group is performed in the candidate group And removing only the interference cancellation technique having the lowest complexity among the interference cancellation schemes remaining in the candidate group if there are more than two interference cancellation schemes remaining in the candidate group.

The method of eliminating inter-relay interference in the cooperative communication system according to the present invention applies ZF scheme, MMSE scheme or MLSE scheme to a cooperative communication system, The performance degradation in the interference environment caused by the interference can be improved.

In addition, the present invention can use a plurality of interference cancellation techniques, so that an optimal cooperative communication system can be selected in realizing a cooperative communication system.

The effects of the present invention are not limited to those mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the following description.

Brief Description of the Drawings Fig. 1 is a system configuration diagram briefly showing a structure of a cooperative communication system.
2 is a graph illustrating BER performance for the interference cancellation technique in the present invention.
3 is a flowchart illustrating a process of selecting an optimal interference cancellation technique according to a communication environment among the ZF scheme, the MMSE scheme, or the MLSE scheme in the present invention.
4 is a flowchart illustrating a procedure of a method for eliminating inter-relay interference in a cooperative communication system according to an exemplary embodiment of the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

The terms first, second, A, B, etc., may be used to describe various components, but the components are not limited by the terms, but may be used to distinguish one component from another . For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. And / or < / RTI > includes any combination of a plurality of related listed items or any of a plurality of related listed items.

As used herein, the singular " include "should be understood to include a plurality of representations unless the context clearly dictates otherwise, and the terms" comprises & , Parts or combinations thereof, and does not preclude the presence or addition of one or more other features, integers, steps, components, components, or combinations thereof.

Before describing the drawings in detail, it is to be clarified that the division of constituent parts in this specification is merely a division by main functions of each constituent part. That is, two or more constituent parts to be described below may be combined into one constituent part, or one constituent part may be divided into two or more functions according to functions that are more subdivided. In addition, each of the constituent units described below may additionally perform some or all of the functions of other constituent units in addition to the main functions of the constituent units themselves, and that some of the main functions, And may be carried out in a dedicated manner.

Hereinafter, a method for eliminating inter-relay interference in a cooperative communication system will be described in detail with reference to the drawings.

Brief Description of the Drawings Fig. 1 is a system configuration diagram briefly showing a structure of a cooperative communication system. Figure 1 illustrates the structure of two cooperative communication systems present in a confined space.

Each of the cooperative communication systems shown in FIG. 1 includes a source node S ₁ , S ₂ having one antenna and two relay nodes S ₁ : R ₁ and R ₂ , S ₂ : R ₃ and R ₄ And shares a destination node having two antennas D ₁ and D ₂ . When a signal is transmitted from the source node to the relay node, the relay nodes transmit signals to the destination node after signal processing.

It can be seen from FIG. ₁ that the signal at the source node S ₂ is transmitted via the relay node to the first antenna D ₁ of the destination node. Since the signal to be received at D ₁ is a signal from S ₁ , the signal from S ₂ acts as an interference. Similarly, since the signal to be received at D2 is a signal from S2, the signal from S1 acts as an interference.

와

,

와

는 각 시스템의 소스 노드와 i번째 릴레이 노드 사이의 채널 계수 및 i번째 릴레이 노드와 목적지 노드 사이의 채널 계수를 의미하고, S1, R1, R2, D1, D2 간의 채널은 h _XY 형태로, S2, R3, R4, D1, D2 간의 채널은 g _XY 형태로 나타내었다. 각 채널 계수는 평균이 0이고 분산이 1인 독립 복소 정규 랜덤 변수로 모형화된다. Also,

Wow

,

Wow

Denotes the channel coefficient between the source node and the i-th relay node of each system and the channel coefficient between the i-th relay node and the destination node, and the channel between S1, R1, R2, D1, h In the _XY form, the channel between S2, R3, R4, D1 and D2 is shown in g _XY form. Each channel coefficient is modeled as an independent complex normal random variable with an average of 0 and a variance of 1.

In the present invention, it is assumed that a channel between each node is quasi-static flat fading and channel coefficients do not change during two orthogonal frequency division multiplexing (OFDM) symbol periods.

The source node S ₁ generates the data symbol blocks X ₁ and X ₂ to be transmitted, and the source node S ₂ generates the data symbol blocks X ₃ and X ₄ . These data symbol blocks are expressed by Equation (1) below.

는 전치행렬 연산 기호를 나타낸다. 먼저 소스 노드 S₁에서는 X₁과 X₂를 아래의 수학식 2와 같은 형태로 조합하여 C₁과 C₂를 생성한다.
Wherein, X _d (k) is a d-th data symbol block of the k-th (k = 1, 2, ... , N-1) phase-shift keying for a subcarrier (phase shift keying: PSK) or phase-quadrature amplitude modulation ( quadrature amplitude modulation (QAM) scheme,

Represents a transpose matrix operation symbol. First, in the source node S ₁ , C ₁ and C ₂ are generated by combining X ₁ and X ₂ in the form of Equation (2) below.

Here, * denotes a conjugate complex calculation symbol. Similarly, in the source node S ₂ , X ₃ and X ₄ are combined as shown in Equation (3) below to generate U ₁ and U ₂ .

Each source node transforms the combinatorial symbol blocks into time domain OFDM samples c _i ( n ) and u _i ( n ) using an inverse discrete Fourier transform (IDFT) with length N (i = 1 , 2). In order to prevent intersymbol interference (ISI) after the IDFT operation, a cyclic prefix (CP) as long as N _G samples is inserted as shown in Equations (4) and (5) below and transmitted to the relay node.

Here, the length N _G of the CP is assumed to be longer than the maximum arrival time error τ that can occur between the paths when the transmission symbol reaches the destination node from the source node through the relay node.

The symbols received i-th in the m-th relay node are expressed by Equation (6) below.

Where P ₁ is the transmit power at the source node S ₁ , P ₃ is the transmit power at the source node S ₂ , w _{i , m} is the mean 0 added to the symbol arriving at the ith relay node, Additive white Gaussian noise (additive white Gaussian noise) means.

Each relay node processes the received symbols as shown in Table 1 below and then transmits them to the destination node. In Table 1, P ₂ is the average transmission power at the relay nodes R ₁ and R ₂ , P ₄ is the average transmission power at the relay nodes R ₃ and R ₄ , and generally P ₁ = 2P ₂ , P ₃ = 2P ₄ .

The result of removing the CP from the signal received at the first antenna D ₁ of the destination node and performing the discrete Fourier transform is shown in Equation (7) below.

Here, C _i ( k ) denotes a DFT output value of c _i ( n ), W _{i , m} ( k ) denotes a DFT output value of w _{i , m} ( n ), and Z _i ( k ) denotes a DFT output value of a noise component. H ₁ ( k ) represents the channel coefficient matrix from the source node S ₁ to the first antenna D ₁ of the destination node, and is defined as Equation (8) below.

I ₁ ( k ) and I ₂ ( k ) denote the DFT output values of the interference components received at D ₁ and are expressed as in Equation 9 below.

Here, U _i ( k ) represents a DFT output value of u _i ( n ), and G ₁ ( k ) represents a channel coefficient matrix from the source node S ₂ to the first antenna D ₁ of the destination node. G ₁ ( k ) is defined as Equation (10) below.

Hereinafter, the interference cancellation algorithm applied in the present invention will be described. ZF technique, MMSE technique and MLSE technique.

ZF  ( Zero Forcing ) technique

The ZF interference cancellation technique eliminates the interference signal using the inverse matrix of the channel coefficient matrix of the system. To when it receives a signal of the first from the second antenna D from the _first source node S ₁ and S ₂ at the destination node, removing the signal from the S ₂ interference signal and detects a signal transmitted from the S ₁ of the desired signal channel The received signal is multiplied by the inverse matrix of the state matrix. The channel coefficient matrix for the symbols received at the destination node is expressed by Equation (11) below.

Here, H ₂ ( k ) and G ₂ ( k ) are channel coefficient matrices from the source node S ₁ and the source node S ₂ to the second antenna D ₂ of the destination node, respectively. The two channel coefficient matrices H ₂ ( k ) and G ₂ ( k ) are defined by the following equations (12) and (13), respectively.

와

를 구하기 위해 목적지 노드에서 수신된 심볼들에 대해 채널 계수 행렬 M(k)의 역행렬을 아래의 수학식 14와 같이 곱해준다.
By using the antennas D ₁ and D ₂ of the destination node, the influence of interference is removed in the cooperative communication system and the estimated values of transmitted symbols C _i ( k ) and U _i ( k )

Wow

The inverse of the channel coefficient matrix M ( k ) is multiplied by the following equation (14) for symbols received at the destination node.

와

를 각각 조합하여 데이터 심볼의 추정치

를 얻으며, 이를 이용하여 복조 과정이 진행된다.
Q _i ( k ) denotes the DFT output value of the received symbol on which the CP removal operation is performed on the second antenna D ₂ of the destination node. Finally,

Wow

To obtain an estimate of the data symbol

And a demodulation process is carried out using this.

MMSE  ( Minimum Mean Square Error )technique

The MMSE interference cancellation technique generates an MMSE filter matrix and multiplies the received symbols at the destination node to obtain the effect of eliminating the influence of interference. Here, the MMSE filter matrix can be expressed by Equation (15) below.

는 허미시안 전치 행렬 (Hermitian transpose matrix) 연산 기호를 의미하며, σ²은 신호 대 잡음비의 (signal-to-noise ratio: SNR) 역수를 의미한다. 목적지 노드에서 수신된 후, CP 제거 연산과 DFT 연산을 거친 심볼들에 MMSE 필터 행렬을 아래의 수학식 16과 같이 곱해준다.
here

Denotes a Hermitian transpose matrix operation symbol, and σ ² denotes a signal-to-noise ratio (SNR) reciprocal of the Hermitian transpose matrix. The MMSE filter matrix is multiplied by the CP removal operation and the DFT operation, as shown in Equation (16) below.

After obtaining the estimated values as described above, the estimated values are finally combined to obtain the estimated values of the original data symbols, and the demodulation process proceeds.

The MMSE algorithm uses a channel coefficient matrix similar to the ZF algorithm, but generates a new filter matrix considering the SNR instead of the inverse of the channel coefficient matrix, thereby multiplying the noise component by the channel instead of completely eliminating the influence of interference. Unlike the ZF algorithm, which does amplify the noise effect rather small, it does not completely remove the influence of the interference, but it reduces the amplification degree of the noise component by adjusting the channel-related values multiplied by the noise component .

MLSE  ( Maximum Likelihood Sequence Estimation ) technique

For example, the MLSE interference cancellation scheme performs convolutional coding on the source node S ₁ and transmits the encoded transmission symbols to the relay nodes R ₁ and R ₂ . In the relay node, after processing as shown in Table 1, it is transmitted to the first antenna D ₁ of the destination node.

와 동일 심볼 비트수를 갖는 송신 가능한 모든 신호의 비트열

상호간의 유클리드 거리를 계산하여 가장 작은 값을 가지는 비트열을 선택한다. 전체 트렐리스 경로의 길이를 L로 했을 경우, 유클리드 거리 A _i는 아래의 수학식 17과 같다.
In D ₁ , after the Alamouti demodulation, a decoding operation is performed using a Viterbi algorithm. That is, in D ₁ , the estimated i-th transmitted bit stream after Alamouti demodulation

And a bit string of all transmittable signals having the same symbol bit number

The Euclidean distances are calculated to select the bit stream having the smallest value. Assuming that the length of the entire trellis path is L, the Euclidean distance A _i is given by Equation 17 below.

In this way, the MLSE algorithm measures 2 ^L Euclidean distances, detects the bit stream having the smallest Euclidean distance value, and corrects errors caused by interference and AWGN in this process. However, when MLSE algorithm is used, the Euclidean distance is calculated considering the number of all cases at the destination node, so that it has higher complexity than ZF algorithm and MMSE algorithm.

Hereinafter, the performance of three interference cancellation techniques applied to the cooperative communication system is compared through simulation. For the performance comparison, the OFDM symbol length and the CP length are set to N = 64 and l _cp = 16, respectively, and the time delay τ is arbitrarily selected from 0 to 15. In case of MLSE, channel coding is performed with code rate 2. The transmission power P ₃ of the interfering signal was compared with the mean value of 100,000 independent measurements after setting it to 6dB.

2 is a graph illustrating BER performance for the interference cancellation technique in the present invention. BER performance due to interference cancellation is shown based on the transmission power P ₁ at the source node 1.

It is confirmed that the performance of the cooperative communication system without the interference cancellation algorithm is seriously degraded in the interference environment. In addition, when three algorithms are applied, BER performance is shown in order of MLSE>MMSE> ZF algorithm. In particular, it can be seen that MLSE exhibits almost the same performance as the cooperative communication system in a non-interference environment. However, it has a high complexity in the order of MLSE>MMSE> ZF. Therefore, if both techniques achieve the target BER at any transmission power, a technique with a lower complexity would be appropriate.

Hereinafter, a method for eliminating inter-relay interference in the cooperative communication system according to the present invention will be summarized.

A method for eliminating inter-relay interference in a cooperative communication system according to an embodiment of the present invention includes the steps of (1) transmitting a signal from a source node to a destination node via a relay node in a cooperative communication system, and (2) Technique, an MMSE technique, or an MLSE technique. In the present invention, interference is removed by applying an optimal technique among a ZF scheme, an MMSE scheme, or an MLSE scheme at a destination node.

In step (2), one of the ZF scheme, the MMSE scheme, and the MLSE scheme is determined based on the reference BER value, the reference communication information, and the complexity of the interference cancellation scheme. And removing the interference. The reference communication information includes at least one of an SNR estimation value or channel coefficient information for MLSE technique application. It is possible to determine whether the MMSE scheme or the MLSE scheme can be used according to the SNR estimation value or the channel information, respectively.

3 is a flowchart illustrating a process of selecting an optimal interference cancellation technique according to a communication environment among the ZF scheme, the MMSE scheme, or the MLSE scheme in the present invention.

In the step of determining the optimal interference cancellation scheme, the MMSE scheme is excluded from the candidate group when the SNR estimation value is not included in the reference communication information in the candidate group including the ZF scheme, the MMSE scheme, and the MLSE scheme. In the case where there are more than two interference cancellation schemes remaining in the candidate group, the interference cancellation technique having an error rate higher than the reference BER value according to the transmission power among the interference cancellation techniques remaining in the candidate group, (S2) of removing the candidate interference group from the candidate group, and (S3) leaving only the interference cancellation technique having the lowest complexity among the remaining interference cancellation techniques remaining in the candidate group if there are more than two interference cancellation techniques remaining in the candidate group.

If only one interference cancellation technique is left in the candidate group in S1, the ZF technique is left. If there are two or more techniques in the candidate group in S1, the reference BER value set by the system or the user in advance is compared with the BER value of the technique remaining in the current candidate group in S2. If there is only one candidate group satisfying the reference BER value, the remaining interference cancellation technique is determined as the optimal interference cancellation technique. If there are two or more remaining interference cancellation techniques, the complexity of the remaining techniques is compared. Finally, Interference cancellation technique. The complexity is the order of the ZF technique <MMSE technique <MLSE technique as described above.

The ZF scheme uses the result obtained by multiplying the received symbol at the destination node by the inverse of the channel coefficient matrix to detect the signal transmitted from the target transmitting node. The MMSE scheme uses a result obtained by multiplying a received symbol at a destination node by an MMSE filter matrix to detect a signal transmitted from a target transmission node. The MLSE scheme is a method in which a symbol node transmitted by convolution coding in a source node is transmitted to a bit stream of a bit stream having the same number of symbol bits as the bit stream transmitted at the ith transmitted bit stream estimated after Alamouti demodulation, And selecting the bit stream having the smallest value is the key. The detailed description is as described above.

4 is a flowchart illustrating a procedure of a method for eliminating inter-relay interference in a cooperative communication system according to another embodiment of the present invention.

As shown in Fig. 4, a method for eliminating inter-relay interference in a cooperative communication system includes the steps of (a) combining two data symbol blocks at a source node, (b) performing inverse Fourier transform (C) transmitting data symbol blocks in a relay node, performing signal processing operations on the data symbol blocks, and transmitting the data symbol blocks to a destination node; (d) removing a cyclic prefix from a data symbol block received from a destination node and performing a Fourier transform (DFT) on the data dumbbell convex, and (e) performing a ZF, MMSE, or MLSE To remove interference.

It is assumed that it has the same structure as the system shown in Fig. The source node is a collaborative communication system that includes a source node S ₁ and a source node S ₂ .

In step (a), S ₁ generates C ₁ and C ₂ represented by combining the two data dummy blocks X ₁ and X ₂ as shown in Equation (2), S ₂ represents two data dummy blocks X ₃ and X ₄ are combined as shown in Equation (3) to generate U ₁ and U ₂ .

In step (b), the source node S ₁ performs an IDFT operation to convert it into a sample c _i (n) in the time domain, inserts a CP having N _G samples in length, and generates a data symbol block s _i , The source node S ₂ performs an IDFT operation to convert it into a sample u _i (n) in the time domain, inserts a CP having N _G samples in length, and generates a data symbol block t _i represented by Equation (5) send.

The data symbol r _{i, m} received at the m-th relay node in the step (c) is expressed by Equation (6), and the operations performed by the relay node are shown in Table 1.

In step (d), the CP is removed from the data symbol block received from the first antenna D ₁ of the destination node, and the result of performing the DFT is expressed by Equation (7).

Step (e) is a step of determining an optimal interference cancellation scheme by using one of ZF scheme, MMSE scheme, and MLSE scheme based on a reference BER value, reference communication information, and complexity of interference cancellation scheme, and applying a technique determined by an optimal interference cancellation scheme And removing the interference. Herein, the reference communication information includes at least one of an SNR estimation value or channel coefficient information for MLSE technique application.

In the step of determining the optimal interference cancellation scheme, the MMSE scheme is excluded from the candidate group when the SNR estimation value is not included in the reference communication information in the candidate group including the ZF scheme, the MMSE scheme, and the MLSE scheme. In the case of two or more interference cancellation schemes remaining in the candidate group, the interference cancellation technique with an error rate higher than the reference BER value according to the transmission power among the interference cancellation techniques remaining in the candidate group is performed in the candidate group And removing only the interference cancellation technique having the lowest complexity among the interference cancellation schemes remaining in the candidate group if there are more than two interference cancellation schemes remaining in the candidate group.

와 S2에서 전송되는 데이터 심볼에 대한 추정치

를 전술한 수학식 14를 통해 산출하고,

와

를 조합하여 최종적인 데이터 심볼에 대한 추정치를 연산한다.In step (e), the ZF scheme estimates the estimate of the data symbol convexity transmitted in S1

And an estimate for the data symbols transmitted in S2

Is calculated through the above-described expression (14)

Wow

To calculate an estimate for the final data symbol.

Here, H ₁ ( k ) denotes a channel coefficient matrix from the source node S ₁ to the first antenna D ₁ of the destination node, H ₂ ( k ) denotes a channel coefficient from the source node S ₁ to the second antenna D ₂ of the destination node G ₂ ( k ) is the channel coefficient matrix from the source node S ₂ to the first antenna D ₁ of the destination node, G ₂ ( k ) is the channel coefficient matrix from the source node S ₂ to the second antenna D ₂ of the destination node matrix and, Y _i (k) is the first antenna two CP removing operation on the second antenna D ₂ of D ₁ CP removal operation is performed the DFT output values of the received symbols in, Q _i (k) is the destination node of the destination node is Is the DFT output value of the received symbol that was performed.

와 S2에서 전송되는 데이터 심볼에 대한 추정치

를 전술한 수학식 16을 통해 산출하고,

와

를 조합하여 최종적인 데이터 심볼에 대한 추정치를 연산한다.In step (e), the MMSE scheme estimates the estimate of the data symbol convexity transmitted in S1

And an estimate for the data symbols transmitted in S2

Is calculated through the above-described expression (16)

Wow

To calculate an estimate for the final data symbol.

과 비트열과 동일 심볼 비트수를 갖는 모든 신호의 비트열

상호 간의 유클리드 거리(A _{i )}를 전술한 수학식 17과 같이 연산하여 가장 작은 값을 갖는 비트열을 선택한다.
In step (e), the MLSE scheme performs convolutional coding on the symbol node transmitted from the source node to the i-th transmitted bit stream estimated after the Alamouti demodulation in the destination node

And a bit string of all signals having the same number of symbol bits as the bit string

The operation as the equation (17) above the mutual Euclidean distance (A _i) between selects a bit string having a smallest value.

It is to be understood that both the foregoing general description and the following detailed description of the present invention are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. It will be understood that variations and embodiments which may occur to those skilled in the art are included within the scope of the present invention.

Claims (17)

(a) transmitting a signal from a source node to a destination node via a relay node in a cooperative communication system; And
(b) removing interference using either the ZF scheme, the MMSE scheme, or the MLSE scheme at the destination node,
In step (b), one of the ZF scheme, the MMSE scheme, and the MLSE scheme may be referred to as an optimal interference scheme based on the reference communication information including the SNR estimation value and the MLSE scheme, the reference BER value, And removing the interferences by applying a technique determined by the optimal interference cancellation technique. delete The method according to claim 1,
The step of determining the optimal interference cancellation technique
If the SNR estimation value does not exist in the reference communication information in the candidate group including the ZF technique, the MMSE technique, and the MLSE technique, the MMSE technique is excluded from the candidate group, and channel coefficient information for application of the MLSE technique is added to the reference communication information Excluding the MLSE technique from the candidate group if the MLSE technique is not available;
Removing the interference cancellation scheme having an error rate higher than the reference BER value according to the transmission power among the interference cancellation schemes remaining in the candidate group when there are more than two interference cancellation schemes remaining in the candidate group; And
And selecting only the interference cancellation technique having the lowest complexity among the interference cancellation schemes remaining in the candidate group if there are more than two remaining interference cancellation schemes remaining in the candidate group. The method according to claim 1,
Wherein the ZF scheme uses a result obtained by multiplying a symbol received at a destination node by an inverse matrix of a channel coefficient matrix to detect a signal transmitted from a target transmission node. The method according to claim 1,
The MMSE technique
A method for eliminating inter-relay interference in a collaborative communication system that uses a result of multiplying a received symbol at a destination node by an MMSE filter matrix to detect a signal transmitted at a destination transmitting node. The method according to claim 1,
The MLSE technique
The Euclidean distance between the bit streams transmitted by the convolutional coding at the source node and the i-th transmitted bit stream estimated after the Alamouti demodulation and the bit streams having the same symbol bit number as the bit stream, And selecting the bit stream having the smallest value by calculation. A method for eliminating interference in a cooperative communication system,
(a) combining two data symbol blocks at a source node;
(b) performing inverse Fourier transform (IDFT) on the data symbol block at the source node, and transmitting the data thumbblock to a relay node by inserting a cyclic prefix (CP);
(c) receiving the data symbol block from the relay node and performing a signal processing operation to transmit the data symbol block to a destination node;
(d) removing the cyclic prefix from a data symbol block received from the destination node and performing a Fourier transform (DFT) on the data dormant convex; And
(e) removing interference using either the ZF scheme, the MMSE scheme, or the MLSE scheme at the destination node,
The source node includes a source node S ₁ and a source node S ₂ ,
The step (e) may include one of the ZF technique, the MMSE technique, or the MLSE technique based on the reference communication information including at least one of the SNR estimation value and the MLSE technique, the reference BER value, and the complexity of the interference cancellation technique. Is determined as an optimal interference cancellation technique and the interference is canceled by applying the technique determined by the optimal interference cancellation technique. 8. The method of claim 7,
In step (a), S ₁ generates C ₁ and C ₂ represented by combining the two data dummy blocks X ₁ and X ₂ as shown in the following equation, and S ₂ represents two data dummy blocks X ₃ and X ₄ To generate U ₁ and U ₂ represented by the following equations.

,

(Where * denotes a conjugate complex arithmetic symbol, and the data dummy block (X _d ) denotes

X _d (k) denotes a modulated data symbol for the kth subcarrier of the dth data block,

Is a transpose matrix operation symbol.) 9. The method of claim 8,
In step (b), the source node S ₁ performs an IDFT operation to convert a time domain sample c _i (n), inserts a CP having N _G sample length, and outputs a data symbol block s _i , The source node S ₂ performs an IDFT operation to convert the time domain sample u _i (n), inserts a CP of N _G sample length, and transmits a data symbol block t _i represented by the following equation A method for eliminating inter-relay interference in a cooperative communication system.

8. The method of claim 7,
Wherein the data symbol (r _{i , m} ) transmitted at the i-th relay in the m-th relay node in the step (c) is expressed by the following equation.

(Where P ₁ is the transmit power at the source node S ₁ , P ₃ is the transmit power at the source node S ₂ , w _{i , m} is the mean 0 added to the symbol arriving at the ith relay node, And S _i denotes a data symbol block transmitted in S ₁ and t _i denotes a data symbol block received in S ₂ ,

Is the channel coefficient between S ₁ and the m-th relay node,

Is the channel coefficient between S ₂ and the m-th relay node) 11. The method of claim 10,
In step (d), the CP is removed from the data symbol block received from the first antenna D ₁ of the destination node, and the result of performing the DFT is expressed by the following equation, where S ₁ is the relay node R ₁ And transmitting a data symbol block to the destination node via R ₂ .

(Wherein, C _i (k) are c _i (n) of the DFT output _value, W _{i, m} (k) are w _{i, m} (n) of the DFT output values, Z _i (k) is a DFT output values of the noise components, H ₁ ( k ) denotes a channel coefficient matrix from the source node S ₁ to the first antenna D ₁ of the destination node, c _i ( n ) denotes a time domain sample in which the IDFT is performed at the source node, P ₂ denotes S ₁ The average transmission power of the relay node to which the data symbol block is transmitted,

Is the channel coefficient of R ₁ and the destination node,

Is the channel coefficient of R ₂ and the destination node) 12. The method of claim 11,
The H ₁ ( k )

A method for eliminating inter-relay interference in a collaborative communication system,
(Where I ₁ ( k ) and I ₂ ( k ) are the DFT output values of interference components received at D ₁ ) delete 8. The method of claim 7,
The step of determining the optimal interference cancellation technique
If the SNR estimation value does not exist in the reference communication information in the candidate group including the ZF technique, the MMSE technique, and the MLSE technique, the MMSE technique is excluded from the candidate group, and channel coefficient information for application of the MLSE technique is added to the reference communication information Excluding the MLSE technique from the candidate group if the MLSE technique is not available;
Removing the interference cancellation scheme having an error rate higher than the reference BER value according to the transmission power among the interference cancellation schemes remaining in the candidate group when there are more than two interference cancellation schemes remaining in the candidate group; And
And selecting only the interference cancellation technique having the lowest complexity among the interference cancellation schemes remaining in the candidate group if there are more than two remaining interference cancellation schemes remaining in the candidate group. 8. The method of claim 7,
The ZF technique
The estimate of the convexity of the data symbol transmitted in S1

And an estimate for the data symbols transmitted in S2

Is calculated by the following equation,

Wow

To calculate an estimate for a final data symbol. &Lt; Desc / Clms Page number 17 &gt;

(Where, H ₁ (k) is the source node, channel coefficient matrix in the S ₁ to the first antenna D destination nodes _1, H ₂ (k) is for the second to the antenna D ₂ channel of the destination node from the source node S ₁ G ₂ ( k ) is a channel coefficient matrix from the source node S ₂ to the first antenna D ₁ of the destination node, G ₂ ( k ) is a channel coefficient matrix from the source node S ₂ to the second antenna D ₂ of the destination node a coefficient matrix, Y _i (k) is the first antenna D ₁ CP removal operation is performed DFT output values of the received symbols in, Q _i (k) is a CP removing operation on the second antenna D ₂ of the destination node in the destination node, Is the DFT output value of the performed received symbol) 8. The method of claim 7,
The MMSE technique
The estimate of the convexity of the data symbol transmitted in S1

And an estimate for the data symbols transmitted in S2

Is calculated by the following equation,

Wow

To calculate an estimate for a final data symbol. &Lt; Desc / Clms Page number 17 &gt;

(Where, H ₁ (k) is the source node, channel coefficient matrix in the S ₁ to the first antenna D destination nodes _1, H ₂ (k) is for the second to the antenna D ₂ channel of the destination node from the source node S ₁ G ₂ ( k ) is a channel coefficient matrix from the source node S ₂ to the first antenna D ₁ of the destination node, G ₂ ( k ) is a channel coefficient matrix from the source node S ₂ to the second antenna D ₂ of the destination node a coefficient matrix, Y _i (k) is the first antenna D ₁ CP removal operation is performed DFT output values of the received symbols in, Q _i (k) is a CP removing operation on the second antenna D ₂ of the destination node in the destination node, Is the DFT output value of the performed received symbol, M _MMSE (k) is the MMSE filter matrix

. 8. The method of claim 7,
The MLSE technique
The symbol node transmitted by convolution coding at the source node is transmitted to the i-th transmitted bit stream estimated after the Alamouti demodulation at the destination node

And a bit string of all signals having the same number of symbol bits as the bit string

A method for eliminating inter-relay interference in a cooperative communication system that calculates a mutual Euclidean distance ( A _{i )} with the following equation to select a bit string having the smallest value.

(Where L is the length of the trellis path).

Images